quickMap: quickMap

In TimiRGeN: Time sensitive microRNA-mRNA integration, analysis and network generation tool

Description

Generates a heatmap of all miRNA:mRNA binding pairs that have been filtered. Pairs are ranked by decreasing correlation.

Usage

quickMap(filt_df, numpairs)

Arguments

filt_df	Dataframe from the matrixFilter function.
numpairs	Number of pairs to plot. Must be an integer more than 1.

Value

Heatmap of miRNA-mRNA pairs.

Examples

library(org.Mm.eg.db)
miR <- mm_miR[1:100,]
mRNA <- mm_mRNA[1:200,]

MAE <- startObject(miR = miR, mRNA = mRNA)

MAE <- getIdsMir(MAE, assay(MAE, 1), orgDB = org.Mm.eg.db, 'mmu')
MAE <- getIdsMrna(MAE, assay(MAE, 2), "useast", 'mmusculus')


MAE <- diffExpressRes(MAE, df = assay(MAE, 1), dataType = 'Log2FC',
                     genes_ID = assay(MAE, 3),
                      idColumn = 'GENENAME',
                      name = "miRNA_log2fc")

MAE <- diffExpressRes(MAE, df = assay(MAE, 2), dataType = 'Log2FC',
                     genes_ID = assay(MAE, 7),
                     idColumn = 'GENENAME',
                     name = "mRNA_log2fc")

Filt_df <- data.frame(row.names = c("mmu-miR-145a-3p:Adamts15",
                                   "mmu-miR-146a-5p:Acy1"),
                     corr = c(-0.9191653, 0.7826041),
                     miR = c("mmu-miR-145a-3p", "mmu-miR-146a-5p"),
                     mRNA = c("Adamts15", "Acy1"),
                     miR_Entrez = c(387163, NA),
                     mRNA_Entrez = c(235130, 109652),
                     TargetScan = c(1, 0),
                     miRDB = c(0, 0),
                     Predicted_Interactions = c(1, 0),
                     miRTarBase = c(0, 1),
                     Pred_Fun = c(1, 1))

MAE <- matrixFilter(MAE, miningMatrix = Filt_df, negativeOnly = FALSE,
                   threshold = 1, predictedOnly = FALSE)

quickMap(filt_df = MAE[[11]], numpairs = 2)

TimiRGeN documentation built on April 17, 2021, 6:03 p.m.